Artificial Fish Schools: Collective Effects of School Size, Body Size, and Body Form (2009)
Hanspeter Kunz, Charlotte K. Hemelrijk, Artificial Intelligence
Abstract Individual-based models of schooling in fish have demonstrated that, via processes of self-organization, artificial fish may school in the absence of a leader or external stimuli, using...
Preface These are the working notes of the workshop on Probabilistic Graphical (2009)
José A. Lozano, Artificial Intelligence
The probabilistic graphical model paradigm has become a popular tool for encoding, representing and handling uncertain knowledge in expert systems over the last decade. Currently, interest is...
In Recent Years, Artificial Intelligence
has been gradually and successfully introduced into Education. However, major challenges remain. Among these, we are concerned how to represent the “knowledge ” of intelligent authoring systems...
AREAS OF SPECIALIZATION (2008)
Robert J. Schalkoff, Lancelot Dr, Fuzzy Systems, Artificial Intelligence, Robert J. Schalkoff
Ann E. Nicholson, Kevin B. Korb, Text Bayesian, Artificial Intelligence, Kevin B. Korb, Ann E. Nicholson
Introduction to Bayesian networks Reasoning with Bayesian networks 11.00 Morning Tea break 11.15 Decision networks Dynamic Bayesian networks
A Formal Tutoring Process Model for Intelligent Tutoring Systems (2008)
Abstract. The combination Computer Based Training systems with
Analysis and Machine Intelligence, ll(5):512-522, May 1989. (2008)
J. K. Aggarwal, J. Y. Aloimonos, I. Weiss, R. T. Chin, E. R. Dougherty, C. R. Giardina, ...
[5] P. Anandan. A., computational framework and an algorithm for the measurement
Feature Selection Based on Adaptive Fuzzy Membership Functions 1) (2008)
Xie Yan-tao, Sang Nong, Zhang Tian-xu, Artificial Intelligence
Abstract Neuro-fuzzy (NF) networks are adaptive fuzzy inference systems (FIS) and have been applied to feature selection by some researchers. However, their rule number will grow exponentially as the...
On-line robot learning using the interval estimation algorithm Tijn van der Zant (2008)
Artificial Intelligence, Marco Wiering
To accomplish a certain goal with a robot many different solutions exist. Usually only one is implemented in a behavior-based architecture (Brooks, 1986; Arkin, 1998), but is it the best one? Since...
Artificial Intelligence and Interactive Entertainment (2007)
Robert St. Amanr, R. Michael Young, As John, Artificial Intelligence
research and computer gaming have quite a bit to offer one another. While many of the most commercially successful computer games have been rather visceral and violent in nature, AI techniques offer...
Comparing Tableaux, Automata and Games for Modal and Temporal Logics (extended abstract) (2007)
Computer Science, Computational Linguistics, Artificial Intelligence, Etc Because
Logics have proved to be a valuable mathematical tool for various areas in
Negotiation Protocols and Dialogue Games Mehdi Dastani Joris Hulstijn Leendert van der Torre (2007)
Artificial Intelligence, De Boelelaan A, Hv Amsterdam
Multi-agent activities often require negotiation. We propose a way to construct exible negotiation protocols, based on
Brian Milch, S. Russel, P. Norvig, Artificial Intelligence, A Modern
• Fundamental task: given observations, make inferences about initially unknown objects • But most RPM languages assume set of objects is fixed and known (Herbrand models) • Bayesian logic...
Rina Dechter, Robert Mateescu, R. Mateescu, Artificial Intelligence
www.elsevier.com/locate/artint
Michael R. Hieb, Ph. D, Engineering Management, Artificial Intelligence, Human Factors, Michael R. Hieb
Affiliate Associate Professor. Technical Expert for the Army on C4I to M&S Interoperability. Architect
Lili Sun, Prakash P. Shenoy, Prakash P. Shenoy, Ronald G. Harper, Distinguished Professor, Artificial Intelligence, ...
This study provides operational guidance for using naïve Bayes Bayesian network (BN) models in bankruptcy prediction. First, we suggest a heuristic method that guides the selection of bankruptcy...
Predicting problems caused by component upgrades (2003)
Stephen Mccamant, Michael D. Ernst, Mit Computer Science, Artificial Intelligence, Lab Technology Square
ABSTRACT We present a new, automatic technique to assess whether replac-ing a component of a software system by a purportedly compatible component may change the behavior of the system. The...
Using Spatial Structure in the AssociativeRetrieval of 2-D Line Drawings (2002)
Patrick W. Yanerashok, K. Goel, Artificial Intelligence, Laboratorycollege Computing, Patrick W. Yaner, Ashok K. Goelartificial
Heterogeneity in the coevolved behaviors of mobile robots: The emergence of specialists (2001)
Mitchell A. Potter, Lisa A. Meeden, Alan C. Schultz, Artificial Intelligence
Many mobile robot tasks can be most efficiently solved when a group of robots is utilized. The type of organization, and the level of coordination and communication within a team of robots affects...
A Bayesian Framework for Case-Based Reasoning (1996)
Edited I. Smith, B. Faltings, Lecture Notes, Artificial Intelligence, Henry Tirri, Petri Kontkanen, ...
. In this paper we present a probabilistic framework for casebased reasoning in data-intensive domains, where only weak prior knowledge is available. In such a probabilistic viewpoint the attributes...
Anton Belov, Automated Reasoning, Artificial Intelligence, Computational Complexity, Zbigniew Stachniak
Postgraduate Scholarship (PGD D), 2006- 2009
Artificial Intelligence, Jaeho Lee, Marcus J. Huber, Edmund H. Durfee, Patrick G. Kenny
The Procedural Reasoning System (PRS) is a general purpose reasoning system that is particularly suited for use in domains in which there are predetermined procedures for handling the situations that...
Eric Bloedorn and Ryszard S. Michalski (1991)
Artificial Intelligence, Eric Bloedorn, Ryszard S. Michalski
This paper presents a method for data-driven constructive induction, which generates new problemoriented attributes by combining the original attributes according to a variety of heuristic rules. The...
Artificial Intelligence, Sct J. Schaeffer, J. Culberson, B. Knight, D. Szafron, Stl J. Schaeffer, ...
f Artificial Intelligence, John Wiley, 2nd Edition, 1992, 224-241. Also available as Tech. Rep. TR 91-10, Dept. of Computing Science, Univ. of Alberta, Edmonton, 1991. [New95] M.M. Newborn, "A...